The decentralized infrastructure for computing in which data, storage, computing, and applications are located between the cloud and data source is known as fog computing. Fog computing brings the power and advantages of the cloud close to where data is created and acted upon, similar to edge computing. These two processes get processing and intelligence closer to data creation; hence many people use edge computing and fog computing interchangeably.
This is done to improve the results and efficiency; however, it might also be done for compliance and security reasons. The term fog originates from the metaphorical term for a cloud close to the ground. It is similar to how the fog concentrates on the network’s edge. The term fog computing is often associated with the Cisco company and is coined by the company’s product line manager. Hence, Cisco fog computing is a registered name, whereas fog computing is open to the community.
Also, fog computing plays a significant role in many fields and has various advantages. So, in this article, we have presented information about its working, benefits, advantages, and disadvantages. Please give it a read, and increase your knowledge about fog computing.
The working of fog computing involves utilizing local devices termed fog nodes and edge devices. Firstly, raw data is collected by IoT beacons, then sent to a fog node close to the data source. Then, the collected information is filtered, analyzed locally, and sent to the cloud for long-term storage if required. There can be many edge devices like routers, cameras, switches, embedded servers, and controllers. However, any device with computing and network connectivity can act as a fog node.
Later, when edge computing resources and IoT devices collect data, it is sent to the local nodes instead of the cloud. Using fog nodes has the advantage of faster data processing when compared to sending requests back to data centers for action and analysis. And in more extensive and distributed networks, the fog nodes are placed in several key areas to analyze and access crucial information locally. Hence, there are many benefits of using a decentralized computing structure.
For example, many security systems use IoT technology to detect theft, break-ins, etc., to notify the authorities. And it could take much time if the alarm warning triggered by the IoT security system needs to be sent to the data center to be analyzed and acted on. Hence, edge computing benefits time-sensitive data like alarms, device status, and fault warnings, as this data needs to be analyzed and acted upon quickly. Cloud computing struggles to give this speed; hence fog computing is used.
There are many benefits of using fog computing, and the main benefits come down to increasing the efficiency of an organization’s computing structure and resources. In most organizations, much critical information I generated at the network’s edge can benefit more than data analytics-related processes. The following are some of the significant benefits of using fog computing in regular use.
Fog computing helps reduce the volume of data sent to the cloud. As a result, it helps to reduce bandwidth consumption and related costs. And the devices and network also perform better with the bandwidth reduction used by fog computing.
The latency is reduced because the initial data processing occurs near the data, and overall responsiveness is improved. Hence, it enables the data to be processed in near-real time, providing millisecond-level responsiveness.
Fog computing generally places compute resources mainly at the LAN level, as opposed to the device level, which is often the case with edge computing. At the same time, fog computing is also network-agnostic, which means that the network can be wired, 5G, or even Wi-Fi.
You need real-time data to maximize the efficiency and accuracy of the insights provided by ML (Machine Learning), as it helps to do real-time data analysis. Hence, real-time data analysis is crucial in IoT security, and fog computing helps.
When we remove the issues of cloud latency from the data processes, it makes them more efficient, and it is offered by fog computing. Hence, the cloud can still be used for data storage, but you don’t need to depend on the cloud for processing.
Fog computing does not require a centralized system; it depends on a network of connected devices. Hence, one can distribute the network across a broader range of locations than traditional computer networking. It leads to a better user experience in the distributed network.
Fog computing is flexible because it can rapidly scale up or down depending on the company’s needs. It is easy to remove, add, or move fog nodes to meet your organization’s current needs and challenges. It facilitates the ability to move computing resources when needed.
Hence, these were the benefits of using fog computing in one’s organization. It is flexible and reduces bandwidth, latency, and many more features. However, there are a few disadvantages, like any other available technology.
There are some disadvantages of fog computing too, which can hamper your company’s costs. The following are some of the main disadvantages of fog computing: –
As fog computing is tied to a physical location, it undermines some of the anytime and anywhere benefits. And these benefits are associated with cloud computing; hence cloud computing can be preferred over fog computing.
Fog computing needs both edge and cloud resources to operate correctly. This means that a vast hardware cost is associated with it, hence is less preferred by companies.
There is still ambiguity around the definition of fog computing, with various vendors defining it differently. However, it has been around for several years and can gain more importance and proper definition shortly
In some cases, fog computing can be subject to security issues, such as IP (Internet Protocol) address spoofing or MitM (man in the middle) attacks. Hence, it appears as a significant disadvantage of fog computing.
Hence, these are the four significant disadvantages of fog computing that must be considered when making any decision regarding fog computing.
Conclusion
Hence, that was all about fog computing, its advantages, disadvantages, and industries which rely on fog computing. One can research more about fog computing and learn various details about it. Fog computing is a powerful technology that processes data collected by IoT devices. Edge and cloud computing can’t expand on a larger scale like the cloud; hence, it can only be used in a smaller region. Therefore, combining fog and cloud computing applications is an excellent opinion for the company’s IoT architecture.
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